Significant breakthroughs have been made in integration of hardware components including processors and memories with faster processing clocks for systems such as game console devices that perform real-time image processing. This enables real-time production of wide variety of realistic images reproduced in every detail, which had been impossible through conventional techniques.
This rapid advancement of the image processing techniques causes typical two-dimensional screens such as television monitors to lag far behind the recent improvements in image quality. For example, standard National Television System Committee (NTSC) television monitors can only display images at low resolutions of around 640 by 448 dots per frame (two fields).
When an image with diagonal edges is displayed especially on a low-resolution two-dimensional screen, these edges extending in a slanting direction appear jagged. Jagged edges are caused because every diagonal edge is built up by square pixels that are stepped on top of one another. These “steps” are called jaggies. Horizontal or vertical edges have no jaggies. Diagonal edges at 45 degrees with respect to the horizontal or vertical axis have the largest number of jaggies when compared among line segments of the same length. More jaggies are visible as the diagonal edge gets closer to 45 degrees. On the other hand, more aliases are visible on diagonal edges closer to the horizontal or vertical. It should be noted that diagonal edges at slight angles against the horizontal or vertical axis have not much jaggies but have a series of step-like patterns, called “aliasing”, which appear more noticeable than on the diagonal edges at 45 degrees.
Taking the above into consideration, systems that process images to be displayed on a two-dimensional screen of a relatively low resolution typically has a function of performing anti-aliasing operation to draw a smooth image without jaggies to an image memory. Anti-aliasing is a technique of making edges in an image appear much smoother or blurring edges to remove aliases on the line.
There are various anti-aliasing techniques, some of which are given below.
(1) First Technique
The percentage of coverage is computed for each pixel on the edge. This percentage of coverage is used as the α value for the blending of the edge with the background. For example, a foreground color pixel Cs is blended with a background color pixel Cd, thereby producing a blended color value C. This is represented by the following equation:C=α*Cs+(1−α)*Cd.
As apparent from the above, the color value C of the pixels for the edge can be given by adding the product of α and Cs (the color value of the pixel in the foreground) to the result of 1 minus α, all multiplied by Cd (the color value of the pixel in the background). This blending provides gradation (multi-scale pixels) on the edge, so that possible aliasing on the edges can be reduced.
(2) Second Technique
The image is rendered at high resolution and then filtered to eventually reduce the number of pixels in the image. For example, the image is rendered at a higher resolution than the display screen. The pixels in the image are then averaged to the final resolution before being copied to the display. This expects to produce effects similar to those obtained by gradation.